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Fitting of the particle size distributions by lognormal functions in the frameworks of empirical classification of the 'aerosol weather' types

机译:在“气溶胶天气”类型的经验分类框架中,逻辑函数的粒度分布拟合

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Variability of the volume distribution functions in the submicron and coarse size ranges in each season and under four type of "aerosol weather": 《background》, 《Haze-S》, 《Smog》 и 《Smoke haze》 is analyzed on the basis of the data on daily mean values of the number concentration of the near-ground atmospheric aerosol obtained by means of an optical counter at the Aerosol Monitoring Station of IAO SB RAS in 2000-2017. The analyzed data arrays were formed in the 《σ_d-P》 coordinates, where σ_d is the scattering coefficient of the aerosol dry matter at the wavelength of λ = 0.51 μm), P is the ratio of the mass concentration of the absorbing substance to the mass concentration of submicron particles. The fitting of the particle volume distribution was carried out as a superposition of two broad lognormal distributions of submicron and coarse particles. The average values of the fitting parameters are presented for all seasons (winter, spring, summer, autumn) and all types of the aerosol weather.
机译:亚微米和粗尺寸范围内的体积分布函数的可变性,在每个季节和四种类型的“气溶胶天气”:“背景”,“雾霾-S”,“烟雾”и“烟雾霾”的基础是在基础上进行分析的通过在2000 - 2017年IAO SB RAS气溶胶监测站的光学计数器获得的近乎磨碎的大气气溶胶数量浓度的每日平均值的数据。分析的数据阵列形成在“σ_d-p”坐标中,其中σ_d是λ=0.51μm波长的气溶胶干物质的散射系数,p是吸收物质的质量浓度与亚微米粒子的质量浓度。颗粒体积分布的配合作为亚微米和粗颗粒的两种宽伐木分布的叠加。为所有季节(冬季,春季,夏季,秋季)和所有类型的气溶胶天气展示了拟合参数的平均值。

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